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Record W7132959240

The Residual Impact of Alfaxalone on GABAA Receptors and on the Electrophysiological Properties of Goldfish Pyramidal Neurons

2023· dissertation· W7132959240 on OpenAlexaboutno aff
Domenic Di Stefano

Bibliographic record

VenueTSpace · 2023
Typedissertation
Language
FieldBiochemistry, Genetics and Molecular Biology
TopicZebrafish Biomedical Research Applications
Canadian institutionsnot available
Fundersnot available
KeywordsGABAA receptorElectrophysiologySedationAgonistGABAA-rho receptorReceptorAnestheticBlockade
DOInot available

Abstract

fetched live from OpenAlex

Alfaxalone is a relatively new anesthetic authorized for use in Canada and my goal is to determine if its impact on neuronal function can be reversed in a sufficiently short timeframe to allow same-day electrophysiological studies in goldfish brain. The goldfish (Carassius auratus) is an anoxia-tolerant vertebrate and is a useful model to study anoxia tolerance mechanisms. Alfaxalone potentiates GABAA receptor currents, and this study aims to identify any long-term impact of whole-animal Alfaxalone sedation on action potential and GABAA receptor properties. I found that following whole-animal sedation with Alfaxalone, that a 3-hour wash of brain slices in Alfaxalone free saline, with saline exchanged every 30 minutes, was required to remove any impact of Alfaxalone on GABAA receptor whole cell currents. In addition, Alfaxalone sedation did not significantly impact action potential properties. These results demonstrate that Alfaxalone is an effective anaesthetic for same-day electrophysiological experiments with goldfish brain slices.

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)0.000
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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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)0.0020.001

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 head0.028
GPT teacher head0.341
Teacher spread0.313 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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