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Record W3203918669 · doi:10.3390/ani11102879

Voluntary Oral Ingestion of a Sedative Prior to Euthanasia with CO2: Behavioural Responses of Mice

2021· article· en· W3203918669 on OpenAlexaff
Raquel Rodriguez-Sanchez, Elyssa Barnaby, Lucía Améndola, Shen-Yan Hea, Bobby Smith, James R. Webster, Gosia Zobel

Bibliographic record

VenueAnimals · 2021
Typearticle
Languageen
FieldVeterinary
TopicAnimal testing and alternatives
Canadian institutionsUniversity of Prince Edward Island
FundersMinistry of Business, Innovation and Employment
KeywordsSedationSedativeMedicineIngestionAnesthesiaInternal medicine

Abstract

fetched live from OpenAlex

Laboratory mice are commonly euthanised with carbon dioxide (CO2); however, there is ample evidence that this gas is aversive. Previous work suggests that sedation achieved via injection with benzodiazepines prior to CO2 administration could reduce aversive behaviours during euthanasia. We explored the potential of using a voluntarily ingested sedative (tiletamine-zolazepam, Zoletil®) prior to euthanasia. Male and female C57BL/6 mice were allocated into one of the five experimental groups, which differed in the dose of Zoletil: 0, 10, 20, 40, 80 or 100 mg/kg. A dose of 20 mg/kg was found to achieve mild sedation prior to euthanasia; mice which received this dose numerically reared and walked on the cage lid less, and showed ataxia, immobility and recumbency for longer than mice that received a lower dose. During euthanasia, mice that received 20 mg/kg showed fewer aversive responses to CO2. Doses of 40 to 100 mg/kg were associated with signs of moderate to severe sedation, but resulted in an incomplete intake of the sedative, which made the interpretation of the aversiveness to CO2 difficult. Voluntary oral administration of a sedative is an effective, affordable, and easy way to minimize the stress of mice to euthanasia with CO2.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.533
Threshold uncertainty score0.445

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.240
GPT teacher head0.417
Teacher spread0.177 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations5
Published2021
Admission routes1
Has abstractyes

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