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Anoxia‐mediated elevation in phasic GABAA receptor currents is essential for anoxia‐tolerance in turtle cortex

2011· article· en· W3177013673 on OpenAlexafffund
David W. Hogg, Leslie T. Buck

Bibliographic record

VenueThe FASEB Journal · 2011
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPainted turtleGABAA receptorDepolarizationNeuroscienceChemistryTurtle (robot)BiologyGABAergicPatch clampGABA receptorNeurotransmissionReceptorElectrophysiologyEndocrinologyInhibitory postsynaptic potentialBiochemistry

Abstract

fetched live from OpenAlex

In mammalian brain, anoxia induces hyper‐excitability and cell death; however, the western painted turtle Chrysemys picta bellii is anoxia tolerant, neuronal activity is depressed by anoxia and cell death does not occur. In anoxic turtle brain [γ‐aminobutyric acid] (GABA) is elevated suggesting that the mechanism(s) responsible for anoxia‐tolerance involve GABAergic synaptic transmission. The objective of this study was to investigate the neuroprotective role of endogenous phasic GABA A receptor currents during anoxia in turtle cortex. Using whole‐cell patch clamp techniques we identified phasic GABA‐mediated IPSC's that double in amplitude with anoxia (41.2 ± 1.6 to 82.1 ± 2.1 pA) resulting in a 60–70% decrease in spontaneous action potential frequency. Inhibition of phasic GABA A receptor currents with gabazine resulted in hyper‐excitability. We conclude that anoxia increases phasic GABA A receptor peak currents resulting in a “shunting current” that prevents further depolarization and hyper‐excitability. Research supported by OGSST grant to DH and NSERC grant to LB.

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 score0.001
Threshold uncertainty score0.002

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)0.0010.000

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 head0.085
GPT teacher head0.347
Teacher spread0.262 · 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
Published2011
Admission routes2
Has abstractyes

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